Aiming at the problems of inadequate user feature extraction, cold start and sparse data, a personalized course recommendation algorithm that utilizes TB-BGAT is suggested. First, the Tiny Bidirectional Encoder Representation from Transformers (TinyBERT) model is utilized to output character-level word vectors; then, Bidirectional Recurrent Neural Network (BiGRU) model is utilized to obtain the embedded contextual semantic features. Finally, the attention mechanism is utilized to allocate weights to various course features by assigning their importance and to obtain the output results. The results of experiment on the publicly available dataset MOOCs-Course prove that the proposed method improves at least 3.62%, 3.04%, and 3.33% in precision, recall, and F1-score, correspondingly, in contrast to several other state-of-the-art course resource recommendation algorithms. The proposed method can enhance the effectiveness of the course recommendation model, enhance the quality of learners' online learning, and provide good technical support for online education learning platforms.
针对用户特征提取不足、冷启动和数据稀疏等问题，提出了一种利用 TB-BGAT 的个性化课程推荐算法。首先，利用Tiny Bidirectional Encoder Representation from Transformers（TinyBERT）模型输出字符级单词向量；然后，利用Bidirectional Recurrent Neural Network（BiGRU）模型获取嵌入式上下文语义特征。最后，利用注意力机制为各种课程特征分配权重，赋予其重要性，从而获得输出结果。在公开数据集 MOOCs-Course 上的实验结果证明，与其他几种最先进的课程资源推荐算法相比，所提出的方法在精确度、召回率和 F1 分数上分别提高了至少 3.62%、3.04% 和 3.33%。所提出的方法可以增强课程推荐模型的有效性，提高学习者的在线学习质量，为在线教育学习平台提供良好的技术支持。
{"title":"TB-BGAT With TinyBERT and BiGRU in Personalized Course Recommendations","authors":"Jing Chen, Weiyu Ye","doi":"10.4018/ijicte.345358","DOIUrl":"https://doi.org/10.4018/ijicte.345358","url":null,"abstract":"Aiming at the problems of inadequate user feature extraction, cold start and sparse data, a personalized course recommendation algorithm that utilizes TB-BGAT is suggested. First, the Tiny Bidirectional Encoder Representation from Transformers (TinyBERT) model is utilized to output character-level word vectors; then, Bidirectional Recurrent Neural Network (BiGRU) model is utilized to obtain the embedded contextual semantic features. Finally, the attention mechanism is utilized to allocate weights to various course features by assigning their importance and to obtain the output results. The results of experiment on the publicly available dataset MOOCs-Course prove that the proposed method improves at least 3.62%, 3.04%, and 3.33% in precision, recall, and F1-score, correspondingly, in contrast to several other state-of-the-art course resource recommendation algorithms. The proposed method can enhance the effectiveness of the course recommendation model, enhance the quality of learners' online learning, and provide good technical support for online education learning platforms.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141643315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Under the background of “Internet plus”, the application of English multi-modal reading teaching mode is of great significance. With the continuous development of Internet technology, the field of education has also been deeply influenced, especially in English reading teaching. Therefore, this study aims to explore how to integrate multi-modal resources into English reading teaching under the background of “Internet plus”. Through literature review and case analysis, it is found that multi-modal reading teaching mode can improve students' reading interest and effectiveness. The results show that the use of images, audio, video and other forms of media resources in the teaching process can help students better understand and absorb English reading materials. Therefore, this paper proposes that in the era of “Internet plus”, teachers should actively design multi-modal English reading teaching activities with the help of various digital media resources, so as to improve students' reading level and ability and promote the development and innovation of English teaching.
{"title":"Application of English Multi-Modal Reading Teaching Mode in the Context of “Internet Plus”","authors":"Wei Guo","doi":"10.4018/ijicte.345932","DOIUrl":"https://doi.org/10.4018/ijicte.345932","url":null,"abstract":"Under the background of “Internet plus”, the application of English multi-modal reading teaching mode is of great significance. With the continuous development of Internet technology, the field of education has also been deeply influenced, especially in English reading teaching. Therefore, this study aims to explore how to integrate multi-modal resources into English reading teaching under the background of “Internet plus”. Through literature review and case analysis, it is found that multi-modal reading teaching mode can improve students' reading interest and effectiveness. The results show that the use of images, audio, video and other forms of media resources in the teaching process can help students better understand and absorb English reading materials. Therefore, this paper proposes that in the era of “Internet plus”, teachers should actively design multi-modal English reading teaching activities with the help of various digital media resources, so as to improve students' reading level and ability and promote the development and innovation of English teaching.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the continuous advancement of educational informatization deepening of teachers' professional development, educational technology ability has become a necessary quality and skill for college teachers. This article introduces the basic concept of the TPACK framework and the design concept of intelligent disciplinary systems and elaborates in detail on how to apply the TPACK framework to the design and development of intelligent disciplinary systems. Through case analysis, this article demonstrates the advantages of intelligent subject systems in improving teaching quality and promoting active learning among students. Finally, this article discusses the future development direction and application prospects of intelligent disciplinary systems. The intelligent subject system based on the TPACK framework provides a new teaching solution for the education field, which helps to promote the process of educational informatization and personalized teaching. Cultivate students' rigorous scientific literacy and good practice habits, and master standardized experimental analysis methods.
{"title":"Design and Application of Intelligent Subject System Based on TPACK Framework","authors":"Lingling Li, Miaomiao Song","doi":"10.4018/ijicte.345931","DOIUrl":"https://doi.org/10.4018/ijicte.345931","url":null,"abstract":"With the continuous advancement of educational informatization deepening of teachers' professional development, educational technology ability has become a necessary quality and skill for college teachers. This article introduces the basic concept of the TPACK framework and the design concept of intelligent disciplinary systems and elaborates in detail on how to apply the TPACK framework to the design and development of intelligent disciplinary systems. Through case analysis, this article demonstrates the advantages of intelligent subject systems in improving teaching quality and promoting active learning among students. Finally, this article discusses the future development direction and application prospects of intelligent disciplinary systems. The intelligent subject system based on the TPACK framework provides a new teaching solution for the education field, which helps to promote the process of educational informatization and personalized teaching. Cultivate students' rigorous scientific literacy and good practice habits, and master standardized experimental analysis methods.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141642946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To address the deficiency in the analysis of individual students within existing research on in-classroom social networks and the constraints of traditional centrality metrics in identifying influential nodes, this paper presents the NEDC-GTOPSIS evaluation method for evaluating node influence in multi-layer heterogeneous networks. Initially, students' friendship, interaction, and attribute information are leveraged to compute neighborhood overlap and attribute similarity between nodes, to construct the Composite Relationship Network. Subsequently, the Seat Similarity Network is constructed by applying the Nearest-Neighbor Effective Distance Criterion to compute seat similarity across various class sessions among nodes. Finally, the structure characteristics of two networks serve as influence decision indicators, and the GRA-TOPSIS algorithm, based on the combined weight method, evaluates nodes' influence. Experiments demonstrate that, compared to traditional single-layer relational networks and classical algorithms, this method can more effectively assess influential student nodes.
{"title":"The NEDC-GTOPSIS Node Influence Evaluation Algorithm Based on Multi-Layer Heterogeneous Classroom Networks","authors":"Zhaoyu Shou, Jinling Xie, Hui Wen, Jinghang Tang, Dongxu Li, Huibing Zhang","doi":"10.4018/ijicte.346822","DOIUrl":"https://doi.org/10.4018/ijicte.346822","url":null,"abstract":"To address the deficiency in the analysis of individual students within existing research on in-classroom social networks and the constraints of traditional centrality metrics in identifying influential nodes, this paper presents the NEDC-GTOPSIS evaluation method for evaluating node influence in multi-layer heterogeneous networks. Initially, students' friendship, interaction, and attribute information are leveraged to compute neighborhood overlap and attribute similarity between nodes, to construct the Composite Relationship Network. Subsequently, the Seat Similarity Network is constructed by applying the Nearest-Neighbor Effective Distance Criterion to compute seat similarity across various class sessions among nodes. Finally, the structure characteristics of two networks serve as influence decision indicators, and the GRA-TOPSIS algorithm, based on the combined weight method, evaluates nodes' influence. Experiments demonstrate that, compared to traditional single-layer relational networks and classical algorithms, this method can more effectively assess influential student nodes.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141640542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing innovative talent cultivation capability. First, by CIPP model (Context, Input, Process and Product Evaluation), an assessment indicator system is built, consisting of 89 indicators in 21 categories. Then, based on indicator characteristics, this paper uses public data statistics, database retrieving, student survey, teacher survey, support personnel and expert investigation, to collect indicator values. After this, by a powerful machine learning algorithm, gradient Boosting regression tree, a capability assessment model is established. And based on collected data, established model is compared with several regression models in innovative talent cultivation capability assessing. Results confirm the performance superiority of our solution.
{"title":"Capability Assessment of Cultivating Innovative Talents for Higher Schools Based on Machine Learning","authors":"Rongjie Huang, Yusheng Sun, Zhifeng Zhang, Bo Wang, Junxia Ma, Yangyang Chu","doi":"10.4018/ijicte.343635","DOIUrl":"https://doi.org/10.4018/ijicte.343635","url":null,"abstract":"The innovation capability largely determines the initiative for future development of a region. Higher school is the main position for training innovative talents. Accurate and comprehensive assessment of innovation cultivation capability is an important basis of higher schools for continuous improvement. Thus, this paper focuses on assessing innovative talent cultivation capability. First, by CIPP model (Context, Input, Process and Product Evaluation), an assessment indicator system is built, consisting of 89 indicators in 21 categories. Then, based on indicator characteristics, this paper uses public data statistics, database retrieving, student survey, teacher survey, support personnel and expert investigation, to collect indicator values. After this, by a powerful machine learning algorithm, gradient Boosting regression tree, a capability assessment model is established. And based on collected data, established model is compared with several regression models in innovative talent cultivation capability assessing. Results confirm the performance superiority of our solution.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140962559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This investigation underscores the significant impact of PE strategy selection on both the cognitive and operational aspects of translation. Highlighting the critical role of PE skills development in translator education, the study proposes several avenues for further research, including broadening participant demographics, integrating diverse and mixed-methods approaches, keeping pace with technological advancements, and engaging in longitudinal studies. These insights offer valuable directions for refining PE methodologies, enhancing translator training programs, and ultimately, elevating the quality of translations.
这项调查强调了 PE 策略选择对翻译认知和操作两方面的重要影响。本研究强调了 PE 技能培养在翻译教育中的关键作用，并提出了几种进一步研究的途径，包括扩大参与者的人口统计、整合多样化的混合方法、跟上技术进步的步伐以及参与纵向研究。这些见解为完善 PE 方法、加强译员培训计划以及最终提高翻译质量提供了宝贵的方向。
{"title":"Optimizing Post-Editing Strategies in Human-Computer Interaction","authors":"Xiaolong Geng","doi":"10.4018/ijicte.343634","DOIUrl":"https://doi.org/10.4018/ijicte.343634","url":null,"abstract":"This investigation underscores the significant impact of PE strategy selection on both the cognitive and operational aspects of translation. Highlighting the critical role of PE skills development in translator education, the study proposes several avenues for further research, including broadening participant demographics, integrating diverse and mixed-methods approaches, keeping pace with technological advancements, and engaging in longitudinal studies. These insights offer valuable directions for refining PE methodologies, enhancing translator training programs, and ultimately, elevating the quality of translations.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140966576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AI chatbots, e.g. ChatGPT, are becoming increasingly popular in education as a means to enhance student learning experiences and improve teaching efficiency. This study utilizes NVivo 12 Plus to examine the role of AI chatbots in education, ethical considerations, and sentimental analysis regarding the utilization of ChatGPT in education. ChatGPT has revolutionized education, but their use raises ethical concerns. They can enhance language learning, but may lead to plagiarism and information overload. Students may not develop discrimination skills and may rely on ChatGPT, leading to concerns about academic dishonesty and a failure to develop cognitive and analytical skills. The use of ChatGPT in clinical education also raises accountability and liability concerns regarding the use of patient information for educational purposes. Guidelines should be established to ensure privacy rights are upheld. Finally, the positive sentiment category was populated by predominantly positive sentiments, followed by neutral and negative sentiments. Future research on ChatGPT in education should focus on its application effectiveness in various educational settings and ethical considerations.
{"title":"ChatGPT in Education","authors":"Song Yang, Ying Dong, Zhong Gen Yu","doi":"10.4018/ijicte.346826","DOIUrl":"https://doi.org/10.4018/ijicte.346826","url":null,"abstract":"AI chatbots, e.g. ChatGPT, are becoming increasingly popular in education as a means to enhance student learning experiences and improve teaching efficiency. This study utilizes NVivo 12 Plus to examine the role of AI chatbots in education, ethical considerations, and sentimental analysis regarding the utilization of ChatGPT in education. ChatGPT has revolutionized education, but their use raises ethical concerns. They can enhance language learning, but may lead to plagiarism and information overload. Students may not develop discrimination skills and may rely on ChatGPT, leading to concerns about academic dishonesty and a failure to develop cognitive and analytical skills. The use of ChatGPT in clinical education also raises accountability and liability concerns regarding the use of patient information for educational purposes. Guidelines should be established to ensure privacy rights are upheld. Finally, the positive sentiment category was populated by predominantly positive sentiments, followed by neutral and negative sentiments. Future research on ChatGPT in education should focus on its application effectiveness in various educational settings and ethical considerations.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140969058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development and the popularization of sports dance, sports dance teaching has become a required elective course in universities. Sports dance can not only improve students' comprehensive quality, but also affect college students' healthy psychology. The use of VR (Virtual Reality) technology in dance education will definitely develop and promote dance education. This paper studies an effective feature extraction method for the characteristics of dance movements based on VR. The edge features of all video images in each segment are accumulated into one image, and the directional gradient histogram features are extracted from it. The results show that compared with the current robust regression method and cascade regression method, our method has higher positioning accuracy on the pollution test set, and more than 75% of the sample errors in this method are within 0.1. This also verifies the effectiveness of this motion recognition algorithm for dance motion recognition. Dance can effectively resist the psychological barriers of college students and improve their comprehensive quality.
{"title":"Influence of VR-Assisted College Dance on College Students' Physical and Mental Health and Comprehensive Quality","authors":"Ziwan Zhao","doi":"10.4018/ijicte.343521","DOIUrl":"https://doi.org/10.4018/ijicte.343521","url":null,"abstract":"With the development and the popularization of sports dance, sports dance teaching has become a required elective course in universities. Sports dance can not only improve students' comprehensive quality, but also affect college students' healthy psychology. The use of VR (Virtual Reality) technology in dance education will definitely develop and promote dance education. This paper studies an effective feature extraction method for the characteristics of dance movements based on VR. The edge features of all video images in each segment are accumulated into one image, and the directional gradient histogram features are extracted from it. The results show that compared with the current robust regression method and cascade regression method, our method has higher positioning accuracy on the pollution test set, and more than 75% of the sample errors in this method are within 0.1. This also verifies the effectiveness of this motion recognition algorithm for dance motion recognition. Dance can effectively resist the psychological barriers of college students and improve their comprehensive quality.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140968956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid development of mobile Internet has brought new development opportunities to college education and teaching. Taking university English teaching as the research object, this paper analyses the characteristics of mobile Internet in the classroom, WeChat platform, English learning app and other forms of teaching, the changes and influence of mobile Internet on English teaching, and its application in university English teaching. According to the actual teaching situation, a comprehensive evaluation system based on the learning process and results was established. The results show that the university English teaching model based on mobile Internet and the innovative evaluation and examination system can effectively improve the teaching efficiency and students' independent and sustainable learning ability. Through the reform of university English teaching, students' academic performance and learning ability have been improved. The research results are of great practical significance for promoting the reform and innovative practice of university English teaching.
{"title":"Reform and Innovation of College English Teaching Under the Background of Mobile Internet and Big Data","authors":"Chaojie Wang, Jie Pan","doi":"10.4018/ijicte.343320","DOIUrl":"https://doi.org/10.4018/ijicte.343320","url":null,"abstract":"The rapid development of mobile Internet has brought new development opportunities to college education and teaching. Taking university English teaching as the research object, this paper analyses the characteristics of mobile Internet in the classroom, WeChat platform, English learning app and other forms of teaching, the changes and influence of mobile Internet on English teaching, and its application in university English teaching. According to the actual teaching situation, a comprehensive evaluation system based on the learning process and results was established. The results show that the university English teaching model based on mobile Internet and the innovative evaluation and examination system can effectively improve the teaching efficiency and students' independent and sustainable learning ability. Through the reform of university English teaching, students' academic performance and learning ability have been improved. The research results are of great practical significance for promoting the reform and innovative practice of university English teaching.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Firstly, this paper analyzes the role of AI in the reading management of English language and literature, establishes the implicit knowledge base of neural network, designs the auxiliary reading system for learning English language and literature, and optimizes the English language and literature management model of AI. The experimental results show that its reading efficiency is increased by 0.48%, and the performance of the credibility model is improved by 0.53% compared with the original system, which greatly optimizes the running time of the system. To some extent, it helps users to manage their time in English language and literature reading, and greatly improves users' reading efficiency and quality. Based on this advantage of AI algorithm, this paper introduces that the algorithm optimizes the reading management model and the training process of neural grid, and constructs a model of English language and literature assisted reading system based on AI. The system can better meet the needs of users in English language and literature reading management.
{"title":"The Role of Artificial Intelligence in English Language and Literature Reading Management","authors":"Xisheng Chen","doi":"10.4018/ijicte.343319","DOIUrl":"https://doi.org/10.4018/ijicte.343319","url":null,"abstract":"Firstly, this paper analyzes the role of AI in the reading management of English language and literature, establishes the implicit knowledge base of neural network, designs the auxiliary reading system for learning English language and literature, and optimizes the English language and literature management model of AI. The experimental results show that its reading efficiency is increased by 0.48%, and the performance of the credibility model is improved by 0.53% compared with the original system, which greatly optimizes the running time of the system. To some extent, it helps users to manage their time in English language and literature reading, and greatly improves users' reading efficiency and quality. Based on this advantage of AI algorithm, this paper introduces that the algorithm optimizes the reading management model and the training process of neural grid, and constructs a model of English language and literature assisted reading system based on AI. The system can better meet the needs of users in English language and literature reading management.","PeriodicalId":55970,"journal":{"name":"International Journal of Information and Communication Technology Education","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141002281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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